Model-Free Change Point Detection for Mixing Processes by Hao Chen, Abhishek Gupta, Yin Sun, Ness Shroff

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Efficacy of Immersive Virtual Reality Combined With Multisensor Biofeedback on Chronic Pain in Fibromyalgia: A Pilot Randomized Controlled Trial by Luca Chittaro, Simone Longhino, Marta Serafini, Sofia Cacioppo, Luca Quartuccio

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SPEMix: a lightweight method via superclass pseudo-label and efficient mixup for echocardiogram view classification by Shizhou Ma, Yifeng Zhang, Delong Li, Yixin Sun, Zhaowen Qiu, Lei Wei, Suyu Dong

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Enhancing leaf disease classification using GAT-GCN hybrid model by Shyam Sundhar, Riya Sharma, Priyansh Maheshwari, Suvidha Rupesh Kumar, T. Sunil Kumar

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AD-Det: Boosting Object Detection in UAV Images with Focused Small Objects and Balanced Tail Classes by Zhenteng Li, Sheng Lian, Dengfeng Pan, Youlin Wang, Wei Liu

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Development of a hip osteoarthritis index for gait quality assessment: a data-driven comparative study by Kamyar Rahmani, Mansour Davoudi, Mohammad Sajjad Alamdar, Rezvan Nasiri

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A Hybrid STL-Deep Learning Framework for Behavioral-Based Intrusion Detection in IoT Environments by Abdullah AlHayan, Jalal Al-Muhtadi

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Classification of Petrographic Thin Section Images With Depthwise Separable Convolution and Dilated Convolution by Shaowei Pan, Xingxing Cheng, Wenjing Fan

“…Additionally, it significantly reduces the parameter count and computational load with only 15.9 million parameters and 1259 billion FLOPs, ensuring efficiency without sacrificing accuracy. …”
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An Ensemble Patient Graph Framework for Predictive Modelling from Electronic Health Records and Medical Notes by S. Daphne, V. Mary Anita Rajam, P. Hemanth, Sundarrajan Dinesh

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Parasitic Contamination and Its Associated Factors in Fruits and Vegetables Collected From Ethiopia’s Local Markets: A Systematic Review and Meta-Analysis by Abayeneh Girma, Aleka Aemiro, Getachew Alamnie, Yitbarek Mulie

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SHM System for Composite Material Based on Lamb Waves and Using Machine Learning on Hardware by Gracieth Cavalcanti Batista, Carl-Mikael Zetterling, Johnny Öberg, Osamu Saotome

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Exploring Transformer-Based Learning for Negation Detection in Biomedical Texts by Ghadeer Althari, Mohammad Alsulmi

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Img2Neuro: brain-trained neural activity encoders for enhanced object recognition by Mona A Aboelnaga, Mohamed W El-Kharashi, Seif Eldawlatly

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Classification of collagen remodeling in asthma using second-harmonic generation imaging, supervised machine learning and texture-based analysis by Natasha N. Kunchur, Joshua J. A. Poole, Jesse Levine, Tillie-Louise Hackett, Rebecca Thornhill, Rebecca Thornhill, Leila B. Mostaço-Guidolin

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Category-Based Sentiment Analysis of Sindhi News Headlines Using Machine Learning, Deep Learning, and Transformer Models by Safdar Ali Soomro, Siti Sophiayati Yuhaniz, Mazhar Ali Dootio, Ghulam Mujtaba, Jawaid Ahmed Siddiqui

“…This work provides a foundational resource for NLP researchers seeking to advance computational methods for Sindhi and similar underrepresented languages.…”
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Multi strategy Horned Lizard Optimization Algorithm for complex optimization and advanced feature selection problems by Marwa M. Emam, Mosa E. Hosney, Reham R. Mostafa, Essam H. Houssein

“…The efficacy of mHLOA is rigorously evaluated using 12 complex benchmark functions from the CEC’22 test suite and 14 standard datasets from the UCI Machine Learning Repository. …”
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Analysis of MCP-Distributed Jammers and 3D Beam-Width Variations for UAV-Assisted C-V2X Millimeter-Wave Communications by Mohammad Arif, Wooseong Kim, Adeel Iqbal, Sung Won Kim

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Trust-driven approach to enhance early forest fire detection using machine learning by Tayyab Khan, Karan Singh, Bhoopesh Singh Bhati, Khaleel Ahmad, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene

“…The proposed UTM system’s core component is the computation of trust ratings for every sensor node. …”
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Privacy-Aware Detection for Large Language Models Using a Hybrid BiLSTM-HMM Approach by Maryam Abbasalizadeh, Sashank Narain

“…It also trains 45.5 times faster than a state-of-the-art framework, offering high computational efficiency without compromising accuracy.…”
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YOLOv8-BS: An integrated method for identifying stationary and moving behaviors of cattle with a newly developed datasetarchive.org by Md Ishtiaq Ahmed, Huiping Cao, Andrés Ricardo Perea, Mehmet Emin Bakir, Huiying Chen, Santiago A. Utsumi

“…Enhanced identification of cattle behavior can significantly improve animal welfare, support preventive health management, and optimize daily operations. Advances in computer vision (CV) and deep learning have shown great potential to enhance the robustness and sophistication of modern animal monitoring systems. …”
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